Transforming Vehicle Insurance Validation with ART360’s Voice Analytics & ITTStar’s GenAI Technology

Executive Summary

The Art 360 task involves handling vehicle insurance documents and ensuring accurate updates and maintenance of information using the Application. This process is critical for maintaining consistency between the details provided by Agents and the information recorded in the Application for the insured vehicle.

The team receives insurance documents, such as binders and declaration pages, from insurance companies or agencies. If any changes or updates are required, they are made directly in the Application. Agents are responsible for contacting insurance company representatives or agencies to verify and update the following key details of the insured customer.

• Effective Date
• Agents Name and Address
• Liability Limits
• Comprehensive and Collusion
• Driver Details (Included and Excluded Drivers)

It is essential for Agents to request the updated declaration page during calls, as it provides comprehensive details about the policy. While binders may contain limited information, the declaration page ensures accuracy and completeness. Even if no updates are required, it is mandatory to ask for the updated declaration page during every call.

Additionally, as part of the audit process, it is important to verify that the updated declaration page was requested during the call. Auditors will also cross-check the information in both the Tool and the Application to ensure accuracy and consistency.

Challenges

1. 1. Time taken for Audio call Quality Analysis
   
   • Due to Multiple Agents working in different time zones making nearly 80 to 100 calls per Agent in a day makes it difficult for a QA to keep a track on the quality of the total calls made and assess the agents.
2. 2. Inconsistent Information Between Documents
   
   • Discrepancies between the binder and declaration page can lead to confusion and require additional follow-up with insurance agencies.
3. 3. Verification of Multiple Details
   
   • Ensuring accuracy for key details such as effective dates, Agents names and addresses, liability limits, and driver information demands meticulous attention to detail.
4. 4. Communication Barriers During Calls
   
   • Miscommunication or lack of clarity from insurance company representatives may lead to incomplete or incorrect updates.
5. 5. Time Constraints
   
   • Calls with insurance agencies and subsequent updates to the Application need to be completed promptly to meet operational deadlines.
6. 6. Ensuring Policy Completeness
   
   • Verifying that all necessary information, such as included and excluded drivers, is recorded and matches agency-provided data requires thorough cross-checking.
7. 7. Accountability for Errors
   
   • Errors in updating or verifying details in the Application or Tool can lead to operational inefficiencies and accountability issues during audits.

Partner Solution

To streamline and enhance vehicle insurance document validation, we developed the ART360 Voice Data Validation Solution, integrating advanced AWS technologies to automate data extraction, transcription, and comparison tasks. This solution leverages cloud-based AI tools and Large Language Models (LLMs) to ensure accuracy and efficiency in compliance workflows.

Key Features Implemented:

• Automated Transcription: Utilizing AWS Transcribe to convert audio call recordings into text, enabling seamless processing of spoken interactions.
• Intelligent Document Processing: Employing AWS Textract to extract key information from scanned insurance documents, ensuring reliable and structured data retrieval.
• Data Validation with LLMs: Integrating AWS Bedrock to query advanced LLMs for comparing and validating data across call transcripts, declaration pages, and Application records, identifying discrepancies efficiently.
• Scalable Cloud Storage: Leveraging AWS S3 for secure storage of audio files, documents, and processed outputs, ensuring scalability and accessibility.
• Comprehensive JSON Outputs: Delivering structured outputs highlighting discrepancies and matches, enabling easy integration into compliance workflows.
• Error Handling and Debugging: Implementing robust error detection to manage missing or mismatched data, ensuring process reliability.

Implementation

• Requirement Analysis: Collaborated with stakeholders to define objectives for insurance data validation and identified key fields to ensure compliance and accuracy across documents and transcripts.
• Technology Setup and Integration: Configured AWS services, including S3, Transcribe, Textract, and Bedrock, to handle storage, transcription, document processing, and LLM-based validation.
• Data Extraction and Processing: Automated transcription of call audio using AWS Transcribe and extracted structured data from scanned insurance documents using AWS Textract.
• Prompt Design and Validation Logic: Developed dynamic prompts to query LLMs via AWS Bedrock for comparing and validating data from transcripts, declaration pages, and Application records
• Storage and Quality Assurance: Organized extracted data and validation results in S3 with clear JSON outputs, implementing automated checks for accuracy and completeness.
• Performance Monitoring and Optimization: Set up monitoring tools to track transcription, extraction, and validation metrics, iteratively refining workflows for improved efficiency and reliability.

Future Enhancements

For future enhancements, we plan to leverage Amazon Nova Vision Models to enhance the accuracy and scalability of data validation and processing tasks. These advanced models will enable deeper contextual understanding and improved performance in analyzing complex insurance data, ensuring seamless integration with existing workflows

Why AWS?

We chose AWS to implement our scraping solution due to its robust and scalable infrastructure, which is essential for handling large volumes of data efficiently. AWS services, particularly Bedrock, provide advanced capabilities for integrating Generative AI (GenAI) into our workflows, allowing for intelligent data analysis and comparison of prospect profiles. The flexibility of AWS ensures seamless integration with various tools, enhancing our ability to gather, process, and store data securely. Additionally, AWS’s commitment to security and compliance reassures us that sensitive business information is protected. Overall, leveraging AWS enables us to create a scalable, efficient, and secure solution that meets the dynamic needs of our marketing teams.

Why choose ITTStar?

Customers and clients should choose our product for several compelling reasons. First, our solution leverages cutting-edge Generative AI technology to intelligently scrape and analyze data, providing accurate and actionable insights that empower marketing teams to make informed decisions. Second, our comprehensive data collection process spans multiple platforms, ensuring a rich and diverse dataset that enhances lead generation efforts. Additionally, our focus on quality assurance guarantees high data accuracy and completeness, minimizing the risk of errors. We also prioritize user-friendly interfaces and training resources, enabling teams to quickly adapt and maximize the benefits of our solution. Finally, our commitment to ongoing support and customization ensures that our product evolves with the changing needs of our clients, making it a reliable partner for achieving business growth was designed to position the legal firm at the forefront of legal tech innovation, optimizing its services and client experiences. 

Results and Impact

The above Solution from ITTStar Consulting, LLC, has significantly impacted our internal QC department, which is focused on maintaining work quality and minimizing errors.

Key points:

• 50% Reduction in Manpower and Costs: Automation of repetitive tasks drastically reduced resource requirements, allowing us to optimize our QC team's efficiency without increasing overhead.
• 99% Increase in Quality Control: Advanced AI-powered validation significantly improved accuracy, reducing process errors and discrepancies.
• Minimized Errors and Escalations: The solution's seamless data validation and proactive error handling have helped maintain high-quality outputs, prevent costly mistakes, and reduce client escalations.

By streamlining our QC operations, ITTStar's solution has enabled us to deliver superior quality while effectively controlling internal costs. It has been a game-changer in modernizing our processes and driving measurable business impact.